The recent FOMC meetings continue to feature a range of debate only around the rate at which the Fed Funds rate can be increased up to about 4% (which has not coincided with a robust economy since the late 1990s). They actually describe this as a 'normal' rate, and the process of raising the rate as 'normalization'. The 'Dot Plot' pictured here indicates the paradigm that the Federal Reserve still believes. Even the most 'dovish' members still think that the Fed Funds rate will be above 2% by 2019.

This is dangerously inaccurate. At the start of 2016, the Federal Reserve expected that they will do four rate likes this year itself. Now they are down to an expectation of just two (one more than the one early in this year), and may just halt with one. How can a collection of supposedly the best and wisest economic forecasters be so consistently wrong? A 20% stock market correction will lead to a swift rate reversal and a 25%+ correction will lead to a resumption of QE in excess of $100B/month.

The -2% indicated by the Wu-Xia shadow rate might be as deep as -4% by 2025, under current trends of technological diffusion. The worldwide central bank easing required to halt deflation by that time will be several times higher than today. As per the ATOM policy reform recommendations, this can be an exceptionally favorable thing if the fundamentals are recognized.

In the ATOM e-book, we examine how technological disruption can be measured, and how the aggregate disruption ongoing in the world at any given time continues along a smooth, exponentially rising trendline. Among these, certain disruptions are invisible to most onlookers, because a tangential technology is simultaneously disrupting seemingly unrelated industries from an orthogonal direction. In that vein, here are two separate lists of industries that are being disrupted, one by Deep Learning and the other by Blockchain.

Note how many industries are present in both of the above lists, meaning that the sectors have to deal with compound disruptions from more than one direction.

In addition, we see that sectors where disruption was artificially thwarted due to excessive regulation and government protectionism merely see a sharper disruption, higher up in the edifice. When the disruption arrives through abstract technologies such as Deep Learning and Blockchain, the incumbents are unlikely to be able to thwart it, due to the source of the disruption being effectively invisible to the untrained eye. What is understood by very few is that the accelerating rate of adoption/diffusion, depicted in this chart here from Blackrock, is enabled by such orthogonal forces that are not tied to any one product category or even industry.